文献类型：期刊文献

英文题名：Data-driven control for discrete-time piecewise affine systems?

作者：Wang, Meng[1];Qiu, Jianbin[2];Yan, Huaicheng[1,4];Tian, Yongxiao[3];Li, Zhichen[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Smart Mfg Energy Chem Proc, Shanghai 200237, Peoples R China;[2]Harbin Inst Technol, Res Inst Intelligent Control & Syst, Harbin 150080, Peoples R China;[3]Shanghai Univ, Sch Artificial Intelligence, Shanghai 200444, Peoples R China;[4]Chengdu Univ, Sch Informat Sci & Engn, Chengdu 610106, Peoples R China

年份：2023

卷号：155

外文期刊名：AUTOMATICA

收录：;EI(收录号：20233014428246);WOS:【SCI-EXPANDED(收录号:WOS:001029043700001)】；

基金：?This work was supported by National Natural Science Foundation of China (NSFC: 62003139, U21B6001, 62273121, 62073143, 62103146, 62173146) . The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Delin Chu under the direction of Editor Ian R. Petersen.

语种：英文

外文关键词：Piecewise affine systems; Data-driven control; Control design; Convex optimization

摘要：This paper studies the problem of data-driven control for discrete-time piecewise affine (PWA) systems. Based on a sequel of sampled control inputs and states with satisfactory rank conditions, the closed loop dynamics of PWA systems can be represented and therefore the explicit information of system matrices is not needed in system stability analysis and controller synthesis processes. First, via S procedure, system stability analysis results have been obtained, and then, two novel data-driven controller design methods in the form of linear matrix inequalities and equations have been proposed such that the resulting closed loop system is asymptotically stable. For PWA systems with unknown state space partition information, an online data-driven control method has been further proposed to guarantee the asymptotic stability of the resulting closed loop systems. Finally, simulation studies of two examples have been given to validate the effectiveness of the proposed data-driven controller design approaches.& COPY; 2023 Elsevier Ltd. All rights reserved.